Chapter 01
Research dimension: Leadership
How does leadership enable AI readiness?
Page 4 of 123 min readPublished Published by Teklens
Leadership enables AI readiness when it brings three things together: visible engagement, secured resources and a vision with goals. In the DACH analysis, engagement scores 3.56 of 5, the second-highest value in the study. Resources (3.11) and vision (3.09) drop almost half a level. The backing is there; what is missing are budget, protected time and a plan.
Contents · Short answer
Three findings
- 01
Backing is the second-highest score in the study
Q1, leadership's engagement in initiating and embedding AI initiatives, reaches 3.56 with a median of 4. Only employees' openness scores higher.[Probst 2026, Appendix B]
- 02
Resources show the second-widest spread
Q2, formal resources and structures such as budgets, protected time or labs, sits at 3.11 with SD 1.27. Some organisations have fixed budgets, many work case by case.[Probst 2026, Appendix B]
- 03
Leadership separates the profiles clearly
The advanced profile reaches 4.58, the intermediate one 3.51, the early stage 2.35. All three pairwise differences are significant (F = 75.6).[Probst 2026, Appendix C]
Evidence
- Q1 Top Management Support3.56
- Q2 Resource Availability3.11
- Q3 Vision & Strategy3.09
Select an item to see its wording, levels and statistics.
Takeaway: Top-management support (Q1, 3.56) is the second-highest score in the study. Resources (Q2, 3.11) and vision (Q3, 3.09) drop almost half a level.
- Unit
- Mean on the maturity scale 1 (least developed) to 5 (most advanced)
- Population
- DACH analysis: 64 cleaned self-assessments from Germany and Switzerland, mostly senior decision-makers
- Denominator
- n = 64 organisations
- Source
- Probst 2026, Appendix B · Appendix B – Mean, standard deviation, median, minimum, maximum and item-rest correlation of all 19 items
Data as a table
| Item | Dimension | M | SD | Median | Min | Max | r (item-rest) |
|---|---|---|---|---|---|---|---|
| Q1 Top Management Support | Leadership | 3.56 | 1.01 | 4.00 | 1 | 5 | 0.71 |
| Q2 Resource Availability | Leadership | 3.11 | 1.27 | 3.00 | 1 | 5 | 0.77 |
| Q3 Vision & Strategy | Leadership | 3.09 | 1.03 | 3.00 | 1 | 5 | 0.78 |
Analysis
Engagement without means
The Leadership dimension holds three factors: top management support, resource availability and vision & strategy. Its mean of 3.26 makes it the second-strongest dimension. Inside the dimension there is a gradient: leadership is engaged, the means and the plan do not keep pace.[Probst 2026, Table 4]
Level 3 on Q1 reads "AI pilots are officially approved; however, AI is not yet a central part of the strategy". Level 4 reads "C-level sends a clear signal; teams receive defined decision-making rights". The median of 4 shows that at least half of the organisations reach that threshold. For resources the median sits at 3: "Project-related budgets and discovery time are available; first formal AI structures exist".[Probst 2026, Appendix A]
The European survey shows the same gradient at a smaller scale: backing 3.52, resources 3.24 (n = 165).[AI Monitor 2026, Europe]
What separates the profiles
Leadership is the dimension where the advanced profile reaches its highest value (4.58). The early stage holds leadership factors "to some degree" too, as the thesis puts it; its 2.35 exceeds its scores for technology (1.95) and adaptability (1.84). Leadership alone therefore does not explain the profiles.[Probst 2026, Table 5]
Teklens interpretation
For your product team
The study describes organisations across sectors. Applying it to software product teams is our interpretation, not an empirical finding about product teams.
Our recommendation for product and engineering leads who have the backing but not the means.
One initiative, one owner, one budget
For the first AI initiative, ask for fixed accountability and a fixed budget instead of a general AI strategy. That is the threshold from level 3 to level 4 on Q2.
Goals in product language
A vision with "defined goals" (level 3 on Q3) can be checked: which Activity should get faster, which decision better? Name the result, not the tool.
Approval stays with people
Decision rights for teams (level 4 on Q1) work when it is clear who approves what. Record the approval in the workflow before agents take on work.
Scope & limits
- 54.7% of responses come from the top leadership level assessing its own engagement. That can pull the Q1 value upwards.
- The three items measure perceived leadership, not budget sizes or documented strategies.
- That advanced organisations show high leadership scores is by construction: the profiles were formed on these same dimensions.
Questions & answers
Does a company need an AI strategy before it starts?
The data show that many organisations start with pilots before a strategy exists (median 3 on vision). What matters is that the pilot produces goals, accountability and budget, otherwise it stays at level 3.
Is leadership engagement the most important factor?
It is one of the eight key factors in the literature, but the thesis finds the sharpest divide between the profiles in adaptability, not in leadership.
What does level 5 on resources look like?
"Resources continuously follow business needs; AI innovation is part of core processes." No special budget any more, just a normal part of product work.
Sources
The DACH analysis comes from Felix Probst's master's thesis (University of St.Gallen, 2026), which focuses on Germany and Switzerland and was written in collaboration with Studyond and Teklens. Teklens and readyai.one ran the European survey as the pre-study for the Swiss AI Monitor; Teklens, as publisher, provides the interpretation. Full citations and the locator index: Methodology & sources.
- Probst 2026 · Probst, F. (2026). Capturing AI's Potential: How Ready Are Organisations in the DACH Region? Master's thesis, University of St.Gallen, in cooperation with Teklens. Germany and Switzerland, n = 64, maturity scale 1–5, self-assessment, exploratory.Locators used: Table 4 and Figure 4, Table 5 and Figure 7, Appendix A, Appendix B, Appendix C
- AI Monitor 2026, Europe · Teklens & readyai.one (2026). AI Monitor 2026 – European survey on organisational AI readiness (pre-study for the Swiss AI Monitor), raw export of 19 August 2026. Research partners: ETH Zürich and University of St.Gallen. Internal aggregate, published on teklens.ai/ai-monitor.
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